{"id":"W2171539929","doi":"10.1109/bibe.2005.22","title":"Discovery of Gene Expression Patterns across Multiple Cancer Types","year":2006,"lang":"en","type":"article","venue":"","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Heuristics; Robustness (evolution); Computer science; Inference; Breast cancer; Computational biology; Gene expression; Machine learning; Gene; Artificial intelligence; Biology; Data mining; Cancer; Genetics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008522203,0.000225745,0.0008014231,0.00250618,0.0004057728,0.0008381906,0.0004410395,0.0004838272,0.0007346411],"category_scores_gemma":[0.002584262,0.0001830759,0.0005333615,0.002285548,0.0004842152,0.0006252558,0.0007653809,0.0005628703,0.0002509223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003494801,"about_ca_system_score_gemma":0.00035065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007795109,"about_ca_topic_score_gemma":0.001103331,"domain_scores_codex":[0.9993554,0.00009911186,0.00003515005,0.0002222584,0.0001917663,0.00009629145],"domain_scores_gemma":[0.9983701,0.0008743316,0.00027479,0.00018652,0.0001932224,0.0001009591],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001096978,0.0002113637,0.5029307,0.0005666031,0.0005300529,0.00111895,0.0006809328,0.008702824,0.2712733,0.003634566,0.0008129454,0.2084409],"study_design_scores_gemma":[0.00005184356,0.0005620827,0.8564492,0.00007521149,0.0006674057,0.002977921,0.001175699,0.04581877,0.0693552,0.01555267,0.00723124,0.00008276547],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9742149,0.001973346,0.02086524,0.0003146385,0.00001600767,0.00003852585,0.0008409653,0.0001145734,0.001621822],"genre_scores_gemma":[0.9881621,0.0005930922,0.009609405,0.00007993211,0.00001997358,0.00003481129,0.001049412,0.00001605373,0.0004350874],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00250618,"threshold_uncertainty_score":0.004507065,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01139483925080868,"score_gpt":0.2772845560376376,"score_spread":0.2658897167868289,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}